nep-cmp New Economics Papers
on Computational Economics
Issue of 2015‒09‒26
six papers chosen by



  1. Assessing policy options for the EU Cohesion Policy 2014-2020 By Andries Brandsma; Francesco Di Comite; Olga Diukanova; D'Artis Kancs; Jesus Lopez Rodriguez; Damiaan Persyn; Lesley Potters
  2. Linearization about the Current State: A Computational Method for Approximating Nonlinear Policy Functions during Simulation By Richard W. Evans; Kerk L. Phillips
  3. Time-Varying Fiscal Multipliers in an Agent-Based Model with Credit Rationing By Mauro Napoletano; Andrea Roventini; Jean-Luc Gaffard
  4. Combined Trust Region with Particle swarm for Multi-objective Optimisation By Zeinab M. H. Hendawy; M. A. El-Shorbagy
  5. Identifying collusion groups using spectral clustering By Suneel Sarswat; Kandathil Mathew Abraham; Subir Kumar Ghosh
  6. Generic technique and the dynamics of technologies: using matroid and design theory to design techniques with systemic impact By Pascal Le Masson; Armand Hatchuel; Olga Kokshagina; Benoit Weil

  1. By: Andries Brandsma (European Commission – JRC - IPTS); Francesco Di Comite (European Commission – JRC - IPTS); Olga Diukanova (European Commission – JRC - IPTS); D'Artis Kancs (European Commission – JRC - IPTS); Jesus Lopez Rodriguez (European Commission – JRC - IPTS); Damiaan Persyn (European Commission – JRC - IPTS); Lesley Potters (European Commission – JRC - IPTS)
    Abstract: In this paper we estimate the impact on GDP of Cohesion Policy 2014-2020 for 267 EU regions running a set of simulations with RHOMOLO, a spatial CGE model tailored for economic analysis at the subnational level. We do so by treating the different parts of Cohesion Policy as exogenous and independent shocks, which are first considered separately and then combined to estimate an overall effect. Our simulation suggests that European regions display significant heterogeneity in their deviations from the baseline due to Cohesion Policy, both in absolute terms and relative to the amounts received.
    Keywords: RHOMOLO; multiregional spatial CGE; Cohesion Policy
    JEL: R13 R58 H54 O32
    Date: 2015–08
    URL: http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc94645&r=all
  2. By: Richard W. Evans (Department of Economics, Brigham Young University); Kerk L. Phillips (Department of Economics, Brigham Young University)
    Abstract: This paper presents an adjustment to commonly used approximation methods for dynamic stochastic general equilibrium (DSGE) models. Policy functions approximated around the steady state will be inaccurate away from the steady state. In some cases, this does not lead to substantial inaccuracies. In other cases, however, the model may not have a well-defined steady state, or the nature of the steady state may be at odds with its off-steady-state dynamics. We show how to simulate a DSGE model by approximating about the current state. Our method introduces an approximation error, but minimizes the error associated with a finite-order Taylor-series expansion of the model’s characterizing equations. This method is easily implemented using available simulation software and has the advantage of mimicking highly non-linear behavior. We illustrate this with a variety of simple models. We compare our technique with other simulation techniques and show that the approximation errors are approximately the same for stable, well-defined models. We also illustrate how this method can solve and simulate models that are not tractable with standard approximation methods.
    Keywords: ynamic stochastic general equilibrium, linearization methods, numerical simulation, computational techniques, simulation modeling, unstable models, unbalanced growth
    JEL: C63 C68 E37
    Date: 2015–09
    URL: http://d.repec.org/n?u=RePEc:byu:byumcl:201502&r=all
  3. By: Mauro Napoletano (OFCE and SKEMA Business School, Sophia-Antipolis (France); Scuola Superiore Sant'Anna, Pisa (Italy)); Andrea Roventini (University of Verona (Italy); Scuola Superiore Sant'Anna, Pisa (Italy); OFCE and SKEMA Business School, Sophia-Antipolis (France)); Jean-Luc Gaffard (OFCE Sciences Po; University of Nice Sophia Antipolis, France; Skema Business School)
    Abstract: We build an agent-based model populated by households with heterogenous and time-varying financial conditions in order to study how fiscal multipliers can change over the business cycle and are aected by the state of credit markets. We find that deficit-spending fiscal policy dampens the effect of bankruptcy shocks and lowers their persistence. Moreover, the size and dynamics of government spending multipliers are related to the degree and persistence of credit rationing in the economy. On the contrary, in presence of balanced-budget rules, output permanently falls below pre-shock levels and the ensuing multipliers fall below one and are much lower than the ones emerging from the deficit-spending policy. Finally, we show that different conditions in the credit market significantly affect the size and the evolution of fiscal multipliers.
    Keywords: Fiscal multipliers, agent-based models, credit-rationing, balance-sheet recession, bankruptcy shocks
    JEL: E63 E21 C63
    Date: 2015–09
    URL: http://d.repec.org/n?u=RePEc:gre:wpaper:2015-30&r=all
  4. By: Zeinab M. H. Hendawy (Menofia University); M. A. El-Shorbagy (Menofia university)
    Abstract: A novel approach is presented to solve multi-objective optimisation problems (MOOP).The algorithm combines the Trust Region (TR) algorithm with the Particle Swarm Optimisation (PSO) method.The MOOP is converted to a single objective optimisation problem (SOOP) using weighted method and some of the points in the search space are generated. For each point, the TR algorithm is used to solve the SOOP to obtain a point on the Pareto frontier. All points obtained are used as particle position for PSO to get all the points on the Pareto frontier. The algorithm is tested using several bench mark problems and coded using MATLAB 7.2 which show successful result in finding a Pareto optimal set.
    Keywords: Multi-objective Optimisation- Trust Region Method- Particle Swarm Optimisation- Weighted Method
    URL: http://d.repec.org/n?u=RePEc:sek:iacpro:2703860&r=all
  5. By: Suneel Sarswat; Kandathil Mathew Abraham; Subir Kumar Ghosh
    Abstract: In an illiquid stock, traders can collude and place orders on a predetermined price and quantity at a fixed schedule. This is usually done to manipulate the price of the stock or to create artificial liquidity in the stock, which may mislead genuine investors. Here, the problem is to identify such group of colluding traders. We modeled the problem instance as a graph, where each trader corresponds to a vertex of the graph and trade corresponds to edges of the graph. Further, we assign weights on edges depending on total volume, total number of trades, maximum change in the price and commonality between two vertices. Spectral clustering algorithms are used on the constructed graph to identify colluding group(s). We have compared our results with simulated data to show the effectiveness of spectral clustering to detecting colluding groups. Moreover, we also have used parameters of real data to test the effectiveness of our algorithm.
    Date: 2015–09
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1509.06457&r=all
  6. By: Pascal Le Masson (CGS - Centre de Gestion Scientifique - MINES ParisTech - École nationale supérieure des mines de Paris); Armand Hatchuel (CGS - Centre de Gestion Scientifique - MINES ParisTech - École nationale supérieure des mines de Paris); Olga Kokshagina (CGS - Centre de Gestion Scientifique - MINES ParisTech - École nationale supérieure des mines de Paris); Benoit Weil (CGS - Centre de Gestion Scientifique - MINES ParisTech - École nationale supérieure des mines de Paris)
    Abstract: As underlined in Arthur’s book “the nature of technology” we are very knowledgeable on the design of objects, services or technical systems, but we don’t know much on the dynamics of technologies. Still contemporary innovation often consists in designing techniques with systemic impact. They are pervasive– both invasive and perturbing-, they recompose the family of techniques. Can we model the impact and the design of such techniques? More specifically: how can one design generic technology, ie a single technology that provokes a complete reordering of families of techniques? Recent advances in design theories open new possibilities to answer these questions. In this paper we use C-K design theory and a matroid-based model of the set of techniques to propose a new model (C-K/Ma) of the dynamics of techniques, accounting for the design of generic technologies. We show: • F1: C-K/Ma offers a computational model for designing a technique with systemic impact. • F2: C-K/Ma accounts for some phenomena associated to generic technology design. • F3: C-K/Ma offers an efficient guide for the design of technologies with systemic impact, based on generativity and genericity criteria
    Keywords: matroid , generic technique ,design theory , generativity
    Date: 2015–07–27
    URL: http://d.repec.org/n?u=RePEc:hal:journl:hal-01154149&r=all

General information on the NEP project can be found at https://nep.repec.org. For comments please write to the director of NEP, Marco Novarese at <director@nep.repec.org>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.